Year: 2024
Type: preprint
Abstract: An outtake from the findnings of a master thesis studying gender bias in course evaluations through the lense of machine learning and nlp. We use different methods to examine and explore the data and find differences in what students write about courses depending on gender of the examiner. Data from English and Swedish courses are evaluated and compared, in order to capture more nuance in the gender bias that might be found. Here we present the results from the work so far, but this is an ongoing project and there is more work to do.
Source: arXiv (Cornell University)
Authors: Lindau, Sarah, Nilsson, Linnea
Institution: Chalmers University of Technology
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4393933642